Utilizing voice and metadata analytics for enhancing performance in a call center

Abstract

A system and methods for utilizing automated machine learning techniques to dynamically analyze historical and current business data including call metadata, dynamically analyze actual voice interactions based on feature vectors associated with voice, and to dynamically utilize the derived information to accurately predict or evaluate business performance.

What is claimed is: 
     
         1 . A computer implemented method for processing business and voice data in a call center, comprising of an Artificial Intelligent Controller utilized to configure, provide logic for, and manage system components and methods to predict or evaluate business outcomes. 
     
     
         2 . The method of  claim 1  wherein processing of business and voice data further comprises an Artificial Intelligent Controller utilized to configure, provide logic for, and manage system components and methods to analyze business and voice data comprising of:
 receiving structured business data; 
 receiving call data and call metadata; 
 determining structured features; 
 generating unstructured data from call data; 
 determining unstructured features; 
 generating derived non-feature data from structured business data, call data and metadata, and unstructured data; 
 generating a raw feature space from structured business data, call data and call metadata, and unstructured data; and 
 generating derived features from existing features in the raw feature space. 
 
     
     
         3 . The method of  claim 1  wherein predict or evaluate business outcomes further comprises use of an Artificial Intelligent Controller utilized to configure, provide logic for, and manage system components and methods to generate inputs for model building comprising of:
 receiving raw feature space; 
 analyzing raw feature space; 
 generating initial feature set comprising of feature vectors generated by raw feature space analysis; 
 associating feature vectors with prediction classes; 
 generating initial data point(s) comprising of a single feature vector aligned with a prediction class, or an aggregate of feature vectors aligned with a prediction class; and 
 generating of initial data point structure comprising of data points(s). 
 
     
     
         4 . The method of  claim 1  wherein predict or evaluate business outcomes further comprises use of an Artificial Intelligent Controller utilized to configure, provide logic for, and manage system components and methods to generate predictive or evaluative model(s) comprising of:
 receiving learning algorithm(s); 
 receiving hyperparameter set(s); 
 configuring learning algorithm; and 
 generating predictive or evaluative model(s). 
 
     
     
         5 . The method of  claim 1  wherein predict or evaluate business outcomes further comprises use of an Artificial Intelligent Controller utilized to configure, provide logic for, and manage system components and methods to generate predictive or evaluative model(s) comprising of:
 receiving initial data point structure; 
 receiving learning algorithm(s); 
 receiving hyperparameter set(s); 
 receiving ensemble technique(s); 
 configuring learning algorithm; and 
 generating predictive or evaluative model(s). 
 
     
     
         6 . The method of  claim 1  wherein predict or evaluate business outcomes further comprises use of an Artificial Intelligent Controller utilized to configure, provide logic for, and manage system components and methods to train predictive or evaluative model(s) comprising of:
 receiving predictive or evaluative model; 
 receiving initial data point structure(s); 
 training predictive or evaluative model(s); and 
 generating predictive or evaluative policy(s). 
 
     
     
         7 . The method of  claim 1  wherein predict or evaluate business outcomes further comprises use of an Artificial Intelligent Controller utilized to configure, provide logic for, and manage system components and methods to generate predictive or evaluative outcome(s) comprising of:
 receiving data point; 
 receiving predictive or evaluative policy; and 
 generating predictive or evaluative outcome(s). 
 
     
     
         8 . The method of  claim 1  wherein predict or evaluate business outcomes further comprises use of an Artificial Intelligent Controller utilized to configure, provide logic for, and manage system components and methods to validate predictive or evaluative policy(s) comprising of:
 receiving predictive or evaluative policy(s); 
 receiving validation data point structure(s); 
 receiving data points; 
 generating outcomes; and 
 generating performance metrics. 
 
     
     
         9 . The method of  claim 1  wherein predict or evaluate business outcomes further comprises use of an Artificial Intelligent Controller utilized to configure, provide logic for, and manage system components and methods to modify predictive or evaluative policy comprising of:
 receiving predictive or evaluative policy; 
 receiving hyperparameter set(s); 
 receiving performance metrics; 
 analyzing hyperparameter(s); 
 modifying hyperparameter; 
 generating new predictive or evaluative model(s); 
 training new predictive or evaluative model(s); 
 generating new predictive or evaluative outcome(s); 
 validating new predictive or evaluative policy(s); 
 comparing new and old predictive or evaluative outcomes; and 
 determining predictive or evaluative policy improvement. 
 
     
     
         10 . The method of  claim 1  wherein predict or evaluate business outcomes further comprises use of an Artificial Intelligent Controller utilized to configure, provide logic for, and manage system components and methods to modify predictive or evaluative policy comprising of:
 receiving predictive or evaluative policy; 
 receiving algorithm ensemble; 
 receiving hyperparameter set(s); 
 receiving performance metrics; 
 adding or deleting algorithm(s); 
 generating new predictive or evaluative model(s); 
 training new predictive or evaluative model(s); 
 generating new predictive or evaluative outcome(s); 
 validating new predictive or evaluative policy(s); 
 comparing new and old predictive or evaluative outcomes; and 
 determining predictive or evaluative policy improvement. 
 
     
     
         11 . The method of  claim 1  wherein predict or evaluate business outcomes further comprises use of an Artificial Intelligent Controller utilized to configure, provide logic for, and manage system components and methods to modify predictive or evaluative policy comprising of:
 receiving predictive or evaluative policy; 
 receiving configured algorithm ensemble; 
 receiving ensemble techniques; 
 receiving performance metrics; 
 evaluating ensemble techniques; 
 generating new predictive or evaluative model(s); 
 training new predictive or evaluative model(s); 
 generating new predictive or evaluative outcome(s); 
 validating new predictive or evaluative policy(s); 
 comparing new and old predictive or evaluative outcomes; and 
 determining predictive or evaluative policy improvement. 
 
     
     
         12 . The method of  claim 1  wherein predict or evaluate business outcomes further comprises use of an Artificial Intelligent Controller utilized to configure, provide logic for, and manage system components and methods to identify a leading candidate predictive or evaluative policy comprising of:
 receiving predictive or evaluative policy; 
 receiving performance metrics; and 
 evaluating performance metrics.